This paper investigates the short-run and long-run effects of financial integration on the dynamics between monetary independence and foreign exchange reserves using a GMM system estimation involving two-year non-overlapping average data (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011) from 114 countries. The results indicate that the effect of foreign exchange reserves on the monetary independence is intensified by the level of financial integration. This suggests a positive spill over effect from the financial integration to the monetary policy independence. Besides, a positive implication of financial integration on monetary independence could be established when the foreign exchange reserves is at the maximum level. In addition, the comparisons between the mean of foreign exchange reserves and the threshold levels of foreign exchange reserves that neutralise the impact of financial integration indicate that on average, the foreign exchange reserves are sufficient to offset the effect of financial integration. A stable exchange rate will undermine the positive impact of foreign exchange reserves on monetary independence. Finally, the long-run and short-run impacts occur in the same direction. This paper ends with some policy implications and suggestions for future research.
Smooth Transition Exponential Smoothing (STES) is a popular exponential smoothing method for volatility forecasting; whereby the success of the STES model lies in the choice of the transition variable. In this paper, three realized variance (RV), daily, weekly and monthly RV were used as the transition variables in STES methods to evaluate the performance of intraday data. While daily squared return is a noisy series, squared residual and daily RV were employed as the proxy for actual volatilities in this study. With five series of exchange rates, a comparative analysis was conducted for Ad Hoc methods, Generalised Autoregressive Conditional Heteroscedastic (GARCH) models, and STES methods using various RV combinations. The empirical results showed that when daily RV was used as proxy for actual volatility, the traditional STES models and STES models with RV as the transition variables outperformed Ad Hoc methods and GARCH models under the RMSE evaluation criteria. Similar promising results were also observed for traditional STES models and STES models with RV as the transition variables under MAE evaluation. The MCS results generally reaffirmed the results from both the MAE and RMSE evaluation criteria.
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